mcpField
P
pyspark-transformer

pyspark-transformer

github.com/jeremylongshoreData & databases2.9k62 installsUpdated 2d ago
Repository

About pyspark-transformer

pyspark-transformer is a skill for PySpark transformer work in data pipelines. It offers step-by-step guidance, code and configuration generation, and validation against common standards.

Key features

  1. 01Step-by-step PySpark transformer guidance
  2. 02ETL and data transformation support
  3. 03Code and configuration generation
  4. 04Validation against common standards

Use cases

  1. 01Developing PySpark data transformations
  2. 02Creating pipeline configurations
  3. 03Getting guidance on streaming workflows

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/jeremylongshore/tons-of-skills-marketplace --skill pyspark-transformer

After installing, type/pyspark-transformerin Claude Code to confirm it loaded.

Details

From the project README

Pyspark Transformer

Overview

This skill provides automated assistance for pyspark transformer tasks within the Data Pipelines domain.

When to Use

This skill activates automatically when you:

  • Mention "pyspark transformer" in your request
  • Ask about pyspark transformer patterns or best practices
  • Need help with data pipeline skills covering etl, data transformation, workflow orchestration, and streaming data processing.

Instructions

  1. Provides step-by-step guidance for pyspark transformer
  2. Follows industry best practices and patterns
  3. Generates production-ready code and configurations
  4. Validates outputs against common standards

Examples

Example: Basic Usage Request: "Help me with pyspark transformer" Result: Provides step-by-step guidance and generates appropriate configurations

Prerequisites

  • Relevant development environment configured
  • Access to necessary tools and services
  • Basic understanding of data pipelines concepts

Output

  • Generated configurations and code
  • Best practice recommendations
  • Validation results

Error Handling

ErrorCauseSolution
Configuration invalidMissing required fieldsCheck documentation for required parameters
Tool not foundDependency not installedInstall required tools per prerequisites
Permission deniedInsufficient accessVerify credentials and permissions

Resources

  • Official documentation for related tools
  • Best practices guides
  • Community examples and tutorials

Related Skills

Part of the Data Pipelines skill category. Tags: etl, airflow, spark, streaming, data-engineering

Comments

Markdown supported